The present invention relates to a method for analyzing video frames and, more particularly, to a time-based evolution method of detecting scene changes in a video.
The automatic analysis of video based on its content has applications in indexing and retrieval of visual information. In particular, the ability to automatically recognize a xe2x80x9cscene changexe2x80x9d in a video can be used to provide a useful index based on scene identity. Previous methods of automatically recognizing a xe2x80x9cscene changexe2x80x9d are based on defining a feature, or a xe2x80x9cdissimilarity measurexe2x80x9d, between two frames. When the dissimilarity measure is xe2x80x9chighxe2x80x9d, the two frames are defined as belonging to different scenes. A quantitative method of defining a xe2x80x9chighxe2x80x9d dissimilarity measure (usually through defining threshold values) is then the basis for defining a scene change. Various prior art algorithms have used histograms, motion and contour information for the features that are studied. A detailed analysis of various prior art approaches to determining scene changes can be found in the article entitled xe2x80x9cScene Break Detection: A Comparisonxe2x80x9d, by G. Lupatini et al. appearing in the Proceedings of the Workshop on Research Issues in Data Engineeringxe2x80x9d, 1998, at pp. 34-41.
Many prior art approaches use techniques such as motion estimation and contour detection and attempt to determine xe2x80x9cinstantxe2x80x9d values to define scene changes. The applied algorithms are based on a two-dimensional analysis of the video, are relatively complex and time-consuming to apply on an on-going basis.
Thus, a need remains in the art for a relatively simple, yet accurate method of detecting scene changes in recorded video.
The need remaining in the prior art is addressed by the present invention, which relates to a method for analyzing video frames and, more particularly, to a time-based evolution method of detecting scene changes in a video.
In accordance with the present invention, a video scene change is defined by creating one-dimensional projections of the video frames. At each spatial location, the time evolution of the one-dimensional projection is considered as a signal and the wavelet transform is calculated. At each time, therefore, the wavelet transforms are one-dimensional signals that can be used to define the high frequency components of the original video. The autocorrelation functions of the high frequency components are then calculated and used as features for scene change detection.
In one embodiment, the time evolution of the one-dimensional features can be displayed as curves. Scene change detection is accomplished by analyzing the shape of the curve.
Other and further features of the present invention will become apparent during the course of the following discussion and by reference to the accompanying drawings.